Published July 31, 2023 | Version v1
Journal article Open

Multivariate analytical approaches for investigating brain-behavior relationships

  • 1. Vanderbilt University
  • 2. McGill University
  • 3. University of Chicago
  • 4. University of Southern California
  • 5. University of Pennsylvania

Description

Background: Many studies of brain-behavior relationships rely on univariate approaches where each variable of interest is tested independently, which does not allow for the simultaneous investigation of multiple correlated variables. Alternatively, multivariate approaches allow for examining relationships between psychopathology and neural substrates simultaneously. There are multiple multivariate methods to choose from that each have assumptions which can affect the results; however, many studies employ one method without a clear justification for its selection. Additionally, there are few studies illustrating how differences between methods manifest in examining brain-behavior relationships. The purpose of this study was to exemplify how the choice of multivariate approach can change brain-behavior interpretations.

Method: We used data from 9,027 9- to 10-year-old children from the Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study®) to examine brain-behavior relationships with three commonly used multivariate approaches: canonical correlation analysis (CCA), partial least squares correlation (PLSC), and partial least squares regression (PLSR). We examined the associations between psychopathology dimensions including general psychopathology, attention-deficit/hyperactivity symptoms, conduct problems, and internalizing symptoms with regional brain volumes.

Results: The results of CCA, PLSC, and PLSR showed both consistencies and differences in the relationship between psychopathology symptoms and brain structure. The leading significant component yielded by each method demonstrated similar patterns of associations between regional brain volumes and psychopathology symptoms. However, the additional significant components yielded by each method demonstrated differential brain-behavior patterns that were not consistent across methods.

Conclusion: Here we show that CCA, PLSC, and PLSR yield slightly different interpretations regarding the relationship between child psychopathology and brain volume. In demonstrating the divergence between these approaches, we exemplify the importance of carefully considering the method's underlying assumptions when choosing a multivariate approach to delineate brain-behavior relationships.

Data availability

Data from the ABCD Study is publicly available through the National Institute of Mental Health Data Archive (https://nda.nih.gov/abcd). The code and corresponding descriptions of the statistical procedures for the current project can be found at https://github.com/VU-BRAINS-lab/ABCD_PLSCCA_Vol.

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Additional details

Identifiers

DOI
10.3389/fnins.2023.1175690
Other
oai:uchicago.tind.io:7062

Funding

National Institute on Drug Abuse
UG3DA045251
National Institute of Mental Health
R01MH098098
National Institute of Mental Health
R01MH117014
National Institute of Mental Health
R00MH117274
National Institute of Mental Health
T32MH18921
National Center for Advancing Translational Sciences
UL1TR000430
National Center for Advancing Translational Sciences
UL1TR000445
Brain & Behavior Research Foundation
Young Investigator Grant
Sloan Research Fellowship
Vanderbilt University
Seeding Success grant
University of Pennsylvania
Lifespan Brain Institute
Children's Hospital of Philadelphia

UChicago Information

Division(s)
Biological Sciences Division, Social Sciences Division
Department(s)
Psychiatry and Behavioral Neuroscience, Psychology, Public Health Sciences
Center(s) or Institute(s)
Neuroscience Institute